Global summary

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively (see Methods for further explanation).

Using data available up to the: 2020-05-02

Note that it takes time for infection to cause symptoms, to get tested for SARS-CoV-2 infection, for a positive test to return and ultimately to enter the case data presented here. In other words, today’s case data are only informative of new infections about two weeks ago. This is reflected in the plots below, which are by date of infection.

Expected daily confirmed cases by country


Figure 1: The results of the latest reproduction number estimates (based on estimated confirmed cases with a date of infection on the 2020-04-22) can be summarised by whether confirmed cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Countries with fewer than 60 confirmed cases reported on a single day are not included in the analysis (light grey) as there is not enough data to reliably estimate the reproduction number.

Summary of latest reproduction number and confirmed case count estimates by date of infection


Figure 1: Confirmed cases with date of infection on the 2020-04-22 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily confirmed cases and shaded based on the expected change in daily confirmed cases. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.

Reproduction numbers over time in the six regions expected to have the most new confirmed cases


Figure 2: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-04-22 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Reported confirmed cases and their estimated date of infection in the six regions expected to have the most new confirmed cases


Figure 3: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-04-22 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Reproduction numbers over time in all regions


Figure 4: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-04-22 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Reported confirmed cases and their estimated date of infection in all regions

Figure 5: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-04-22 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Latest estimates (as of the 2020-04-22)

Table 1: Latest estimates (as of the 2020-04-22) of the number of confirmed cases by date of infection, the effective reproduction number, and the doubling time (when negative this corresponds to the halving time) in each region. The mean and 90% credible interval is shown.
Country/Region New confirmed cases by infection date Expected change in daily cases Effective reproduction no. Doubling/halving time (days)
Afghanistan 174 (134 – 204) Increasing 1.4 (1.2 – 1.6) 9.3 (6.6 – 16)
Algeria 177 (147 – 212) Increasing 1.3 (1.1 – 1.4) 13 (8.6 – 28)
Argentina 164 (131 – 191) Increasing 1.2 (1 – 1.3) 24 (12 – 1100)
Armenia 74 (52 – 93) Unsure 1.1 (0.9 – 1.3) 62 (13 – -22)
Australia 15 (5 – 24) Unsure 0.9 (0.5 – 1.4) -110 (7.3 – -6.6)
Austria 76 (54 – 94) Unsure 1 (0.8 – 1.3) 78 (14 – -21)
Azerbaijan 45 (30 – 61) Unsure 1.1 (0.9 – 1.4) 29 (8.6 – -21)
Bahrain 111 (83 – 134) Unsure 1 (0.8 – 1.1) -42 (32 – -13)
Bangladesh 631 (566 – 687) Increasing 1.2 (1.1 – 1.3) 16 (12 – 27)
Belarus 1019 (940 – 1093) Increasing 1.2 (1.1 – 1.3) 20 (15 – 30)
Belgium 704 (626 – 762) Decreasing 0.8 (0.7 – 0.8) -14 (-21 – -11)
Bolivia 66 (45 – 84) Likely increasing 1.2 (1 – 1.4) 34 (10 – -27)
Bosnia and Herzegovina 49 (30 – 64) Likely increasing 1.2 (0.9 – 1.4) 17 (7.4 – -49)
Brazil 6548 (6288 – 6751) Increasing 1.4 (1.3 – 1.4) 10 (9.5 – 11)
Bulgaria 59 (41 – 78) Unsure 1.1 (0.9 – 1.2) -1e+05 (14 – -15)
Cameroon 67 (45 – 86) Unsure 0.9 (0.7 – 1.1) -23 (43 – -9.2)
Canada 1805 (1691 – 1906) Likely increasing 1 (1 – 1.1) 150 (48 – -130)
Chile 766 (693 – 834) Increasing 1.3 (1.2 – 1.4) 13 (10 – 18)
China 12 (3 – 19) Unsure 0.9 (0.4 – 1.4) -35 (7.1 – -5.2)
Colombia 320 (274 – 358) Increasing 1.2 (1.1 – 1.3) 19 (12 – 46)
Cote dIvoire 39 (23 – 53) Unsure 1 (0.8 – 1.2) -39 (16 – -9)
Croatia 15 (6 – 24) Likely decreasing 0.7 (0.4 – 1) -8.7 (33 – -3.8)
Cuba 38 (23 – 52) Likely decreasing 0.9 (0.7 – 1.1) -27 (22 – -8.3)
Czechia 80 (56 – 101) Unsure 1 (0.8 – 1.2) -69 (20 – -13)
Democratic Republic of the Congo 34 (18 – 46) Increasing 1.4 (1.1 – 1.7) 10 (5 – -480)
Denmark 166 (132 – 195) Unsure 1 (0.8 – 1.1) -250 (28 – -23)
Djibouti 19 (7 – 28) Likely decreasing 0.7 (0.4 – 1.1) -11 (20 – -4.4)
Dominican Republic 255 (211 – 291) Likely increasing 1.1 (1 – 1.2) 29 (14 – -420)
Ecuador 1788 (1643 – 1929) Increasing 1.2 (1.1 – 1.4) 14 (8 – 48)
Egypt 304 (262 – 350) Increasing 1.2 (1.1 – 1.4) 14 (9.7 – 27)
Equatorial Guinea 20 (9 – 30) Unsure 1 (0.6 – 1.4) -20 (12 – -5.5)
Estonia 14 (5 – 23) Unsure 0.9 (0.6 – 1.2) -27 (9.5 – -5.5)
Finland 120 (94 – 149) Unsure 1 (0.9 – 1.2) 660 (20 – -20)
France 1352 (1268 – 1451) Decreasing 0.9 (0.8 – 1) -23 (-46 – -16)
Germany 1095 (1010 – 1172) Decreasing 0.7 (0.6 – 0.8) -9.6 (-12 – -8.2)
Ghana 178 (145 – 209) Increasing 1.5 (1.3 – 1.7) 7.1 (5.4 – 10)
Greece 23 (10 – 33) Likely decreasing 0.8 (0.5 – 1.1) -8 (-460 – -4)
Guinea 117 (87 – 142) Increasing 1.3 (1.1 – 1.4) 16 (8.5 – 82)
Guinea Bissau 43 (27 – 60) Increasing 2.6 (1.8 – 3.3) 3.1 (2.3 – 4.8)
Honduras 42 (25 – 56) Increasing 1.3 (1 – 1.6) 14 (6.4 – -62)
Hungary 82 (62 – 105) Unsure 1 (0.8 – 1.1) -150 (19 – -15)
Iceland 2 (0 – 6) Unsure 0.8 (0 – 1.6) -0.41 (0.64 – -0.14)
India 2015 (1891 – 2133) Increasing 1.2 (1.1 – 1.2) 23 (18 – 33)
Indonesia 354 (305 – 399) Unsure 1 (0.9 – 1.1) 150 (29 – -47)
Iran 1201 (1118 – 1290) Unsure 1 (1 – 1.1) 220 (49 – -86)
Iraq 81 (59 – 102) Increasing 1.4 (1.1 – 1.7) 9.2 (5.8 – 22)
Ireland 422 (373 – 474) Decreasing 0.8 (0.8 – 0.9) -18 (-37 – -12)
Israel 158 (125 – 188) Decreasing 0.7 (0.6 – 0.9) -9.2 (-16 – -6.4)
Italy 2274 (2150 – 2395) Decreasing 0.9 (0.9 – 1) -33 (-55 – -23)
Japan 254 (215 – 291) Decreasing 0.8 (0.7 – 0.9) -13 (-24 – -9.1)
Kazakhstan 215 (180 – 253) Increasing 1.2 (1.1 – 1.4) 15 (9.6 – 39)
Kosovo 12 (4 – 20) Decreasing 0.7 (0.4 – 0.9) -5.9 (-39 – -3.2)
Kuwait 270 (230 – 307) Increasing 1.3 (1.1 – 1.4) 14 (9.5 – 27)
Kyrgyzstan 15 (6 – 24) Likely decreasing 0.9 (0.6 – 1.2) -22 (11 – -5.4)
Latvia 13 (5 – 22) Unsure 1.1 (0.7 – 1.4) 100 (6 – -7)
Lebanon 6 (1 – 11) Unsure 1.2 (0.6 – 1.7) 75 (3.6 – -4.2)
Lithuania 16 (5 – 24) Unsure 0.9 (0.5 – 1.4) -120 (7.2 – -6.3)
Luxembourg 19 (8 – 29) Unsure 0.9 (0.5 – 1.2) -17 (14 – -5.3)
Malaysia 64 (44 – 81) Unsure 1 (0.8 – 1.2) 120 (13 – -17)
Maldives 81 (58 – 101) Increasing 1.9 (1.5 – 2.3) 5.1 (3.8 – 7.7)
Mexico 1283 (1185 – 1368) Increasing 1.2 (1.1 – 1.3) 22 (16 – 35)
Moldova 141 (113 – 171) Unsure 1 (0.9 – 1.2) 320 (21 – -24)
Morocco 112 (81 – 133) Decreasing 0.8 (0.7 – 0.9) -14 (-43 – -8.4)
Netherlands 453 (397 – 504) Decreasing 0.7 (0.7 – 0.8) -12 (-17 – -9.2)
New Zealand 2 (0 – 6) Unsure 1.3 (0.2 – 2.3) -1.1 (1.7 – -0.25)
Niger 9 (2 – 15) Unsure 1.1 (0.4 – 1.7) 69 (4.5 – -5.3)
Nigeria 188 (152 – 221) Increasing 1.4 (1.2 – 1.6) 10 (7 – 18)
North Macedonia 24 (10 – 34) Unsure 0.9 (0.6 – 1.1) -42 (11 – -7.4)
Norway 59 (40 – 75) Unsure 0.9 (0.7 – 1.1) -39 (23 – -11)
Oman 105 (78 – 127) Unsure 1 (0.9 – 1.2) 60 (14 – -27)
Pakistan 979 (893 – 1052) Increasing 1.2 (1.1 – 1.3) 20 (14 – 31)
Palestine 20 (8 – 30) Likely increasing 1.3 (0.9 – 1.7) 19 (5.5 – -14)
Panama 215 (177 – 248) Likely increasing 1.1 (1 – 1.2) 40 (16 – -90)
Peru 2774 (2627 – 2906) Increasing 1.3 (1.2 – 1.4) 12 (11 – 14)
Philippines 270 (227 – 306) Increasing 1.2 (1.1 – 1.3) 17 (11 – 42)
Poland 364 (318 – 407) Unsure 1 (0.9 – 1.1) 84 (25 – -64)
Portugal 374 (321 – 418) Decreasing 0.9 (0.8 – 1) -22 (-57 – -14)
Puerto Rico 54 (35 – 70) Increasing 1.4 (1.1 – 1.8) 6.8 (4.4 – 15)
Qatar 894 (813 – 965) Increasing 1.2 (1.1 – 1.2) 23 (16 – 39)
Romania 356 (310 – 401) Unsure 1 (0.9 – 1.1) 150 (28 – -44)
Russia 7288 (7055 – 7510) Increasing 1.2 (1.1 – 1.2) 22 (19 – 26)
Saudi Arabia 1480 (1383 – 1563) Increasing 1.1 (1.1 – 1.2) 27 (19 – 43)
Senegal 74 (50 – 92) Increasing 1.4 (1.1 – 1.6) 13 (7.1 – 91)
Serbia 280 (234 – 317) Likely increasing 1.1 (1 – 1.2) 36 (17 – -220)
Singapore 743 (677 – 806) Decreasing 0.9 (0.9 – 1) -32 (-92 – -19)
Slovakia 5 (1 – 11) Decreasing 0.4 (0.2 – 0.6) -2.5 (-5.3 – -1.6)
Somalia 48 (30 – 63) Likely increasing 1.2 (0.9 – 1.5) 19 (7.4 – -40)
South Africa 308 (261 – 347) Increasing 1.2 (1.1 – 1.4) 17 (11 – 38)
South Korea 11 (2 – 18) Unsure 1.1 (0.5 – 1.6) 130 (5.4 – -5.9)
Spain 1158 (1065 – 1239) Decreasing 0.6 (0.6 – 0.7) -7 (-8.1 – -6.2)
Sri Lanka 41 (25 – 57) Likely increasing 1.2 (1 – 1.5) 29 (8.4 – -20)
Sudan 58 (38 – 75) Increasing 1.5 (1.2 – 1.9) 7.8 (4.9 – 20)
Sweden 707 (643 – 767) Likely increasing 1.1 (1 – 1.1) 58 (26 – -250)
Switzerland 159 (129 – 190) Likely decreasing 0.9 (0.7 – 1) -30 (120 – -13)
Thailand 10 (2 – 16) Likely decreasing 0.8 (0.5 – 1) -7.6 (30 – -3.4)
Tunisia 13 (3 – 20) Unsure 1.1 (0.6 – 1.5) 43 (5.5 – -7.3)
Turkey 2889 (2753 – 3023) Decreasing 0.9 (0.9 – 1) -41 (-140 – -24)
Ukraine 276 (236 – 314) Decreasing 0.8 (0.7 – 0.9) -12 (-18 – -8.5)
United Arab Emirates 612 (553 – 673) Increasing 1.1 (1 – 1.2) 34 (19 – 130)
United Kingdom 5276 (5088 – 5476) Increasing 1.1 (1 – 1.1) 54 (37 – 99)
United Republic of Tanzania 52 (32 – 68) Increasing 1.5 (1.1 – 1.9) 7.3 (4.2 – 27)
United States of America 30053 (29447 – 30531) Increasing 1 (1 – 1) 74 (51 – 130)
Uzbekistan 46 (28 – 62) Unsure 1 (0.7 – 1.2) -320 (12 – -11)